docs: def predict_from_cfg(cls, df, cfgname):
          """
          Parameters
          ----------
          df : DataFrame
              The dataframe which contains the columns to use for the estimation.
          cfgname : string
              The name of the yaml config file which describes the hedonic model.
  
          Returns
          -------
          predicted : pandas.Series
              Predicted data in a pandas Series. Will have the index of `data`
              after applying filters and minus any groups that do not have
              models.
          hm : RegressionModel which was used to predict
          """
          logger.debug('start: predict from configuration {}'.format(cfgname))
          hm = cls.from_yaml(str_or_buffer=cfgname)
  
          price_or_rent = hm.predict(df)
          print(price_or_rent.describe())
  
          logger.debug('start: predict from configuration {}'.format(cfgname))
          return price_or_rent, hm